Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add PostHog/posthog-foss --skill maintaining-python-testsgit clone --depth 1 https://github.com/PostHog/posthog-fossWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/posthog/posthog-foss/maintaining-python-tests)<a href="https://agentmods.dev/skills/posthog/posthog-foss/maintaining-python-tests"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/maintaining-python-tests/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/posthog/posthog-foss/maintaining-python-tests"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/maintaining-python-tests.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00110 | $0.02048 |
| Opus 5.5 | $0.00044 | $0.00819 |
| Sonnet 5.5 | $0.00022 | $0.00410 |
| Haiku 4.5 | $0.00011 | $0.00205 |
Grade A, and why
maintaining-python-tests scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maintaining Python tests
Before you propose a change to how the suite runs in CI, check things already tried. It records measured verdicts on test parallelism, sharding, and coverage-based selection, so a rejected approach is not rebuilt.
Use this skill for an existing Python test suite. Use /writing-tests before adding or substantially changing coverage. Use /fixing-flaky-tests when intermittent failure is the main problem.
The goal is not a smaller test count. The goal is a suite that catches the same realistic regressions with less compute, less waiting, and less maintenance.
Principles
- Measure before changing code. Rank tests by total observed work, not by one slow local run.
- Preserve behavior coverage. Keep cases that exercise different validation, persistence, integration, or output paths.
- Remove only expired or redundant coverage. Get explicit approval before deleting a test.
- Share expensive infrastructure, not mutable test state. Preserve isolation with unique IDs, schemas, tables, topics, or tenants.
- Measure after merge. Local results prove the mechanism. Fresh master data proves the result in CI.
- Separate testcase work from suite wall time. A change can reduce summed testcase time and not change the slowest pytest suite.
Read measurement.md before you query timing data or report an improvement. Read optimization-patterns.md when you select a fix.
Workflow
1. Define the result
Write down the user problem before choosing a test:
- Reduce total test compute.
- Reduce the slowest pytest suite.
- Remove expired maintenance burden.
- Restore test ownership.
- Reduce repeated external-service setup.
These results need different measurements. Do not claim faster CI when only summed test call time decreased.
2. Rank current work
Use recent PostHog test spans from master when available. Start with a complete window after the latest relevant merge.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 214 lines · 110 tokens per session scan A e87edd7ca2fb
maintaining-python-tests is a skill published in the GitHub repository PostHog/posthog-foss (724 stars, last pushed today), licensed MIT. It adds 110 tokens to every session and 2,048 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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